Fetching the paper…
Reading the bibliography…
To foster the development of pedagogically potent and ethically sound AI-integrated learning landscapes, it is pivotal to critically explore the perceptions and experiences of the users immersed in these contexts.
1910
Earlier work this paper cites.
I. Ajzen, The theory of planned behavior, Organizational behavior and human decision processes 50 (2) (1991) 179–211
1991
Earlier work this paper cites.
C. P. Smith, J. W. Atkinson, D. C. McClelland, J. Veroff, et al., Motivation and personality: Handbook of thematic content analysis, Cambridge University Press, 1992
1992
Earlier work this paper cites.
doi:10.1207/s15327019eb1103_2
D. L. McCabe, L. K. Trevino, K. D. Butterfield, Cheating in academic institutions: A decade of research , Ethics & Behavior 11 (3) (2001) 219–232 · 2001
Earlier work this paper cites.
S. Yang, Y. Wang, X. Chu, A survey of deep learning techniques for neural machine translation (2020) · 2002
Earlier work this paper cites.
M. Prince, Does active learning work? a review of the research, Journal of engineering education 93 (3) (2004) 223–231
2004
Earlier work this paper cites.
B. Noonan, C. R. Duncan, Peer and self-assessment in high schools, Practical Assessment, Research, and Evaluation 10 (1) (2005) 17
2005
Earlier work this paper cites.
doi:10.1191/1478088706qp063oa
V. Braun, V. Clarke, Using thematic analysis in psychology , Qualitative Research in Psychology 3 (2) (2006) 77–101 · 2006
Earlier work this paper cites.
doi:10.1145/1753846.1754122
B. Lin, E. M. Huang, Reuse: Promoting repurposing through an online diy community , in: CHI ’10 Extended Abstracts on Human Factors in Computing Systems, CHI EA ’10, Association for Computing Machinery, New York, NY, USA, 2010, p. 4177–4182 · 2010
Earlier work this paper cites.
M. Forehand, Bloom’s taxonomy, Emerging perspectives on learning, teaching, and technology 41 (4) (2010) 47–56
2010
Earlier work this paper cites.
doi:10.1109/rita.2013.2258225
M. L. Nistal, An experience of continuous assessment in telecommunication technologies engineering: New costs for the teacher , IEEE Revista Iberoamericana de Tecnologias del Aprendizaje 8 (2) (2013) 90–95 · 2013
Earlier work this paper cites.
doi:10.1111/bjet.12228
K.-H. Cheng, C.-C. Tsai, The interaction of child-parent shared reading with an augmented reality (AR) picture book and parents' conceptions of AR learning , British Journal of Educational Technology 47 (1) (2014) 203–222 · 2014
Earlier work this paper cites.
A. L. Culén, A. Følstad, Innovation in hci: What can we learn from design thinking?, in: Proceedings of the 8th nordic conference on human-computer interaction: Fun, fast, foundational, 2014, pp. 849–852
2014
Earlier work this paper cites.
doi:10.1007/978-3-031-02217-3
A. Blandford, D. Furniss, S. Makri, Qualitative HCI Research , Springer International Publishing, 2016 · 2016
Earlier work this paper cites.
doi:10.1109/iccsp.2017.8286763
K. Baktha, B. K. Tripathy, Investigation of recurrent neural networks in the field of sentiment analysis , in: 2017 International Conference on Communication and Signal Processing (ICCSP), IEEE, 2017 · 2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, I. Polosukhin, Attention Is All You Need , arXiv:1706.03762 [cs] (Dec. 2017) · 2017
Earlier work this paper cites.
A. Seldon, O. Abidoye, The fourth education revolution, Legend Press Ltd, 2018
2018
Earlier work this paper cites.
doi:10.1007/978-3-030-01689-0_23
F. Clarizia, F. Colace, M. Lombardi, F. Pascale, D. Santaniello, Chatbot: An education support system for student , in: Cyberspace Safety and Security, Springer International Publishing, 2018, pp. 291–302 · 2018
Earlier work this paper cites.
doi:10.1109/iicspi.2018.8690387
L. Yao, Y. Guan, An improved LSTM structure for natural language processing , in: 2018 IEEE International Conference of Safety Produce Informatization (IICSPI), IEEE, 2018 · 2018
Earlier work this paper cites.
GDPR, The european union’s general data protection regulation (April 2018). URL https://gdpr-info.eu/
2018
Earlier work this paper cites.
doi:10.1145/3290605.3300864
M. Xia, M. Sun, H. Wei, Q. Chen, Y. Wang, L. Shi, H. Qu, X. Ma, Peerlens: Peer-inspired interactive learning path planning in online question pool , in: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI ’19, Association for Computing Machinery, New York, NY, USA, 2019, p. 1–12 · 2019
Earlier work this paper cites.
doi:10.1016/j.jacr.2019.05.050
A. Chetlen, R. Artrip, B. Drury, A. Arbaiza, M. Moore, Novel use of chatbot technology to educate patients before breast biopsy , Journal of the American College of Radiology 16 (9) (2019) 1305–1308 · 2019
Earlier work this paper cites.
L. Dong, N. Yang, W. Wang, F. Wei, X. Liu, Y. Wang, J. Gao, M. Zhou, H.-W. Hon, Unified language model pre-training for natural language understanding and generation , in: H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, R. Garnett (Eds.), Advances in Neural Information Processing Systems, Vol. 32, Curran Associates, Inc., 2019. URL https://proceedings.neurips.cc/paper_files/paper/2019/file/c20bb2d9a50d5ac1f713f8b34d9aac5a-Paper.pdf
2019
Earlier work this paper cites.
Z. Yang, Z. Dai, Y. Yang, J. Carbonell, R. R. Salakhutdinov, Q. V. Le, Xlnet: Generalized autoregressive pretraining for language understanding , in: H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, R. Garnett (Eds.), Advances in Neural Information Processing Systems, Vol. 32, Curran Associates, Inc., 2019. URL https://proceedings.neurips.cc/paper_files/paper/2019/file/dc6a7e655d7e5840e66733e9ee67cc69-Paper.pdf
2019
Earlier work this paper cites.
K. Hao, Openai has released the largest version yet of its fake-news-spewing ai (August 2019). URL https://www.technologyreview.com/2019/08/29/133218/openai-released-its-fake-news-ai-gpt-2/
2019
Earlier work this paper cites.
doi:10.1145/3290605.3300881
J. A. Pater, L. E. Reining, A. D. Miller, T. Toscos, E. D. Mynatt, "notjustgirls": Exploring male-related eating disordered content across social media platforms , in: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI ’19, Association for Computing Machinery, New York, NY, USA, 2019, p. 1–13 · 2019
Earlier work this paper cites.
A. of Internet Researchers (AoIR), Internet research: Ethical guidelines 3.0 (April 2019). URL https://aoir.org/ethics/
2019
Earlier work this paper cites.
doi:10.1145/3290605.3300698
A. S. M. Noman, S. Das, S. Patil, Techies against facebook: Understanding negative sentiment toward facebook via user generated content , in: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI ’19, Association for Computing Machinery, New York, NY, USA, 2019, p. 1–15 · 2019
Earlier work this paper cites.
doi:10.1145/3396956.3398260
M. J. Ahn, Y.-C. Chen, Artificial intelligence in government: Potentials, challenges, and the future , in: The 21st Annual International Conference on Digital Government Research, dg.o ’20, Association for Computing Machinery, New York, NY, USA, 2020, p. 243–252 · 2020
Earlier work this paper cites.
doi:10.1145/3406865.3418326
J. Liu, L. Loh, E. Ng, Y. Chen, K. L. Wood, K. H. Lim, Self-evolving adaptive learning for personalized education , in: Conference Companion Publication of the 2020 on Computer Supported Cooperative Work and Social Computing, CSCW ’20 Companion, Association for Computing Machinery, New York, NY, USA, 2020, p. 317–321 · 2020
Earlier work this paper cites.
doi:10.1145/3366423.3380127
J. Li, S. Shang, L. Shao, Metaner: Named entity recognition with meta-learning , in: Proceedings of The Web Conference 2020, WWW ’20, Association for Computing Machinery, New York, NY, USA, 2020, p. 429–440 · 2020
Earlier work this paper cites.
doi:10.18653/v1/2020.emnlp-demos.6
T. Wolf, L. Debut, V. Sanh, J. Chaumond, C. Delangue, A. Moi, P. Cistac, T. Rault, R. Louf, M. Funtowicz, J. Davison, S. Shleifer, P. von Platen, C. Ma, Y. Jernite, J. Plu, C. Xu, T. L. Scao, S. Gugger, M. Drame, Q. Lhoest, A. Rush, Transformers: State-of-the-art natural language processing , in: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Association for Computational Linguistics, 2020 · 2020
Cited alongside, same era.
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, D. Amodei, Language models are few-shot learners , in: H. Larochelle, M. Ranzato, R. Hadsell, M. Balcan, H. Lin (Eds.), Advances in Neural Information Processing Systems, Vol. 33, Curran Associates, Inc., 2020, pp. 1877–1901. URL https://proceedings.neurips.cc/paper_files/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf
2020
Cited alongside, same era.
doi:10.1017/s1351324920000601
R. Dale, GPT-3: What’s it good for? , Natural Language Engineering 27 (1) (2020) 113–118 · 2020
Cited alongside, same era.
doi:10.1016/j.ijhcs.2022.102922
F. M. Calisto, N. Nunes, J. C. Nascimento, Modeling adoption of intelligent agents in medical imaging , International Journal of Human-Computer Studies 168 (2022) 102922 · 2022
Later among the works it cites.
doi:10.1111/ejed.12533
W. Holmes, I. Tuomi, State of the art and practice in ai in education , European Journal of Education 57 (4) (2022) 542–570 · 2022
Later among the works it cites.
doi:10.1016/j.caeai.2022.100074
H. Khosravi, S. B. Shum, G. Chen, C. Conati, Y.-S. Tsai, J. Kay, S. Knight, R. Martinez-Maldonado, S. Sadiq, D. Gašević, Explainable artificial intelligence in education , Computers and Education: Artificial Intelligence 3 (2022) 100074 · 2022
Later among the works it cites.
doi:10.1145/3487553.3524202
E.-U. Haq, T. Braud, L.-H. Lee, A. K. Vallapuram, Y. Yu, G. Tyson, P. Hui, Short, colorful, and irreverent! a comparative analysis of new users on wallstreetbets during the gamestop short-squeeze , in: Companion Proceedings of the Web Conference 2022, WWW ’22, Association for Computing Machinery, New York, NY, USA, 2022, p. 52–61 · 2022
Later among the works it cites.
doi:10.1145/3491140.3528279
H. Xia, H. X. Ng, Z. Chen, J. Hollan, Millions and billions of views: Understanding popular science and knowledge communication on video-sharing platforms , in: Proceedings of the Ninth ACM Conference on Learning @ Scale, L@S ’22, Association for Computing Machinery, New York, NY, USA, 2022, p. 163–174 · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
doi:10.1145/3313831.3376768
M. Tahaei, K. Vaniea, N. Saphra, Understanding privacy-related questions on stack overflow , in: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, CHI ’20, Association for Computing Machinery, New York, NY, USA, 2020, p. 1–14 · 2020
Cited alongside, same era.
doi:10.1145/3313831.3376723
A. Tyack, E. D. Mekler, Self-determination theory in hci games research: Current uses and open questions , in: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, CHI ’20, Association for Computing Machinery, New York, NY, USA, 2020, p. 1–22 · 2020
Cited alongside, same era.
doi:10.1145/3410404.3414259
K. Boustani, A. C. Tally, Y. R. Kim, C. Nippert-Eng, Gaming the name: Player strategies for adapting to name constraints in online videogames , in: Proceedings of the Annual Symposium on Computer-Human Interaction in Play, CHI PLAY ’20, Association for Computing Machinery, New York, NY, USA, 2020, p. 120–131 · 2020
Cited alongside, same era.
doi:10.1155/2021/8812542
X. Zhai, X. Chu, C. S. Chai, M. S. Y. Jong, A. Istenic, M. Spector, J.-B. Liu, J. Yuan, Y. Li, A review of artificial intelligence (AI) in education from 2010 to 2020 , Complexity 2021 (2021) 1–18 · 2021
Cited alongside, same era.
G.-J. Hwang, C.-Y. Chang, A review of opportunities and challenges of chatbots in education , Interactive Learning Environments (2021) 1–14 doi:10.1080/10494820.2021.1952615
2021
Cited alongside, same era.
doi:10.1109/icicv50876.2021.9388633
E. Kasthuri, S. Balaji, A chatbot for changing lifestyle in education , in: 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), IEEE, 2021 · 2021
Cited alongside, same era.
doi:10.1145/3449086
R. H. Mogavi, X. Ma, P. Hui, Characterizing student engagement moods for dropout prediction in question pool websites , Proceedings of the ACM on Human-Computer Interaction 5 (CSCW1) (2021) 1–22 · 2021
Cited alongside, same era.
doi:10.1016/j.jmig.2021.02.011
R. Sinha, R. Shibata, A. Patel, J. A. Sternchos, Social media in minimally invasive gynecologic surgery: What is #trending on instagram? , Journal of Minimally Invasive Gynecology 28 (10) (2021) 1730–1734 · 2021
Cited alongside, same era.
doi:10.1145/3430895.3460126
R. Hadi Mogavi, Y. Zhao, E. Ul Haq, P. Hui, X. Ma, Student barriers to active learning in synchronous online classes: Characterization, reflections, and suggestions , in: Proceedings of the Eighth ACM Conference on Learning @ Scale, L@S ’21, Association for Computing Machinery, New York, NY, USA, 2021, p. 101–115 · 2021
Cited alongside, same era.
Later among the works it cites.
doi:https://doi.org/10.1016/j.chb.2022.107529
E. Yi-No Kang, D.-R. Chen, Y.-Y. Chen, Associations between literacy and attitudes toward artificial intelligence–assisted medical consultations: The mediating role of perceived distrust and efficiency of artificial intelligence , Computers in Human Behavior 139 (2023) 107529 · 2022
Later among the works it cites.
doi:10.1016/j.caeai.2022.100061
W. Yang, Artificial intelligence education for young children: Why, what, and how in curriculum design and implementation , Computers and Education: Artificial Intelligence 3 (2022) 100061 · 2022
Later among the works it cites.
doi:10.1016/j.chb.2023.107721
C.-Y. Wang, J. J. Lin, Utilizing artificial intelligence to support analyzing self-regulated learning: A preliminary mixed-methods evaluation from a human-centered perspective , Computers in Human Behavior 144 (2023) 107721 · 2023
Closest in time.
doi:10.1145/3539597.3575784
S. C. Hoi, Responsible ai for trusted ai-powered enterprise platforms , in: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, WSDM ’23, Association for Computing Machinery, New York, NY, USA, 2023, p. 1277–1278 · 2023
Closest in time.
T. Bianchi, Global weekly interest in chatgpt on google search 2022-2023 (March 2023). URL https://www.statista.com/statistics/1366930/chatgpt-google-search-weekly-worldwide/?locale=en
2023
Closest in time.
D. Ruby, Chatgpt statistics for 2023 (new data + gpt-4 facts) (March 2023). URL https://www.demandsage.com/chatgpt-statistics/
2023
Closest in time.
OpenAI, Gpt-4 technical report (2023) · 2023
Closest in time.
doi:10.1016/j.iotcps.2023.04.003
P. P. Ray, ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope , Internet of Things and Cyber-Physical Systems 3 (2023) 121–154 · 2023
Closest in time.
doi:10.1016/j.ijinfomgt.2023.102642
Opinion paper: “so what if ChatGPT wrote it?” multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy , International Journal of Information Management 71 (2023) 102642 · 2023
Closest in time.
doi:10.1145/3544548.3580682
F. M. Calisto, J. Fernandes, M. Morais, C. Santiago, J. M. Abrantes, N. Nunes, J. C. Nascimento, Assertiveness-based agent communication for a personalized medicine on medical imaging diagnosis , in: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, ACM, 2023 · 2023
Closest in time.
doi:10.1109/access.2023.3268224
A. Shoufan, Exploring students’ perceptions of ChatGPT: Thematic analysis and follow-up survey , IEEE Access 11 (2023) 38805–38818 · 2023
Closest in time.
W. Luo, H. He, J. Liu, I. R. Berson, M. J. Berson, Y. Zhou, H. Li, Aladdin’s genie or pandora’s box for early childhood education? experts chat on the roles, challenges, and developments of ChatGPT , Early Education and Development (2023) 1–18 doi:10.1080/10409289.2023.2214181
2023
Closest in time.
doi:10.1145/3563359.3596996
E. Murgia, M. S. Pera, M. Landoni, T. Huibers, Children on chatgpt readability in an educational context: Myth or opportunity? , in: Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, UMAP ’23 Adjunct, Association for Computing Machinery, New York, NY, USA, 2023, p. 311–316 · 2023
Closest in time.
K. Kikerpill, A. Siibak, App-hazard disruption: An empirical investigation of media discourses on ChatGPT in educational contexts , Computers in the Schools (2023) 1–22 doi:10.1080/07380569.2023.2244941
2023
Closest in time.
I. Twitter, Twitter api (January 2023). URL https://developer.twitter.com/en/docs/twitter-api
2023
Closest in time.
I. Reddit, Reddit api (January 2023). URL https://www.reddit.com/dev/api/
2023
Closest in time.
I. Google, Youtube data api (March 2023). URL https://developers.google.com/youtube/v3
2023
Closest in time.
I. LinkedIn, Linkedin api products (January 2023). URL https://developer.linkedin.com/product-catalog
2023
Closest in time.
D. Ruby, Twitter statistics for marketers in 2023 (users & trends) (March 2023). URL https://www.demandsage.com/
2023
Closest in time.
D. Ruby, Reddit statistics for 2023 (users & traffic data) (March 2023). URL https://www.demandsage.com/
2023
Closest in time.
D. Ruby, Youtube statistics (2023) — trending facts & figures shared! (January 2023). URL https://www.demandsage.com/
2023
Closest in time.
D. Ruby, Important linkedin statistics for 2023 (data & trends) (March 2023). URL https://www.demandsage.com/
2023
Closest in time.
A. S. S. D. GmbH, A computer-assisted qualitative data analysis software (February 2023). URL https://atlasti.com
2023
Closest in time.
S. Conroy, What countries is chat gpt available & not available in? (April 2023). URL https://www.wepc.com/tips/what-countries-is-chat-gpt-unavailable/
2023
Closest in time.
B. Foroughi, M. G. Senali, M. Iranmanesh, A. Khanfar, M. Ghobakhloo, N. Annamalai, B. Naghmeh-Abbaspour, Determinants of intention to use ChatGPT for educational purposes: Findings from PLS-SEM and fsQCA , International Journal of Human–Computer Interaction (2023) 1–20 doi:10.1080/10447318.2023.2226495
2023
Closest in time.